Quantum Techniques in Machine Learning

Abstract

s 9 Marco Loog — Surrogate Losses in Classical Machine Learning (Invited Talk) . . . 11 Minh Ha Quang — Covariance matrices and covariance operators in machine learning and pattern recognition: A geometrical framework (Invited Talk) . . . . . . 12 Jonathan Romero, Jonathan Olson, Alan Aspuru-Guzik — Quantum autoencoders for efficient compression of quantum data . . . . . . . . . . . . . . . . . . 13 Iris Agresti, Niko Viggianiello, Fulvio Flamini, Nicolò Spagnolo, Andrea Crespi, Roberto Osellame, Nathan Wiebe, and Fabio Sciarrino — Pattern recognition techniques for Boson Sampling Validation . . . . . . . . . . . . . . . . . 15 J. Wang, S. Paesani, R. Santagati, S. Knauer, A. A. Gentile, N. Wiebe, M. Petruzzella, A. Laing, J. G. Rarity, J. L. O’Brien, and M. G. Thompson — Quantum Hamiltonian learning using Bayesian inference on a quantum photonic simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Luca Innocenti, Leonardo Banchi, Alessandro Ferraro, Sougato Bose and Mauro Paternostro — Supervised learning of time independent Hamiltonians for gate design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Davide Venturelli — Challenges to Practical End-to-end Implementation of Quantum Optimization Approaches for Combinatorial problems (Invited Talk) . . . . . . 22 K. Imafuku, M. Hioki, T. Katashita, S. Kawabata, H. Koike, M. Maezawa, T. Nakagawa, Y. Oiwa, and T. Sekigawa — Annealing Computation with Adaptor Mechanism and its Application to Property-Verification of Neural Network Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Simon E. Nigg, Niels Niels Lörch, Rakesh P. Tiwari — Robust quantum optimizer with full connectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 William Cruz-Santos, Salvador E. Venegas-Andraca and Marco Lanzagorta — Adiabatic quantum optimization applied to the stereo matching problem . . . . . 26 Alejandro Perdomo Ortiz — Opportunities and Challenges for Quantum-Assisted Machine Learning in Near-Term Quantum Computers . . . . . . . . . . . . . . . . . 27 Christopher J. Turner, Konstantinos Meichanetzidis, Zlatko Papić, and Jiannis K. Pachos — Distinguishing free and interacting as pattern recognition . . 28 Konstantinos Meichanetzidis, Christopher J. Turner, Ashk Farjami, Zlatko Papić, and Jiannis K. Pachos — Free-fermion descriptions of parafermion chains and string-net models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Ashk Farjami — Identifying Free Particle Correlations in Topologically Ordered Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Ivan Glasser, Nicola Pancotti, Moritz August, Ivan D. Rodriguez, and J. Ignacio Cirac — Neural Networks Quantum States, String-Bond States and chiral topological states . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Raban Iten, Roger Colbeck, and Matthias Christandl — Quantum Circuits for Quantum Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Seth Lloyd — Prospects in Quantum Machine Learning (Invited Talk) . . . . . . . 38 Jiannis Pachos — Knots, Computation and Quantum Physics (Invited Talk) . . . 39